A Branch-and-Price Algorithm for a Team Orienteering Problem with Fixed-Wing Drones

TL;DR

This paper introduces a specialized branch-and-price algorithm for optimizing routes of fixed-wing drones in a team orienteering problem, considering their unique kinematic constraints, and demonstrates its effectiveness through computational experiments.

Contribution

It develops a novel branch-and-price algorithm tailored to fixed-wing drone constraints within the team orienteering problem, advancing solution methods for this complex routing challenge.

Findings

Algorithm effectively solves benchmark instances to optimality.

Fixed-wing constraints significantly impact routing solutions.

Computational results validate the algorithm's efficiency.

Abstract

This paper formulates a team orienteering problem with multiple fixed-wing drones and develops a branch-and-price algorithm to solve the problem to optimality. Fixed-wing drones, unlike rotary drones, have kinematic constraints associated with them, thereby preventing them to make on-the-spot turns and restricting them to a minimum turn radius. This paper presents the implications of these constraints on the drone routing problem formulation and proposes a systematic technique to address them in the context of the team orienteering problem. Furthermore, a novel branch-and-price algorithm with branching techniques specific to the constraints imposed due to fixed-wing drones are proposed. Extensive computational experiments on benchmark instances corroborating the effectiveness of the algorithms are also presented.